Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Even though annotations already declare readOnlyHint=true, the description adds a significant behavioral caveat: data comes from the local IndexedDB cache and only includes channels synced by Slack Desktop. This is critical for setting expectations about data freshness and completeness, going beyond the annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Three concise, front-loaded sentences deliver all key information without redundancy. The most important facts (purpose, data source limitation, workspace filtering) are presented in order, and no sentence is wasted.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's low complexity, optional parameters, existing output schema, and clear annotations, the description covers every practical concern: what is listed, data source caveat, and how to scope the query. It is complete for an agent to select and invoke the tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema already fully documents both parameters (limit and workspace_id), so the description does not add much semantic value. It repeats the workspace_id source from the schema without introducing new meaning, aligning with the baseline for high schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states a specific action ('Lists channels in a Slack workspace') and enumerates the channel types included (public, private, DMs). It distinguishes this from sibling tools like slack_read_channel_messages by focusing on listing channels, not reading messages.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context: it reads from a local cache and instructs to pass workspace_id from slack_list_workspaces to filter, establishing a sequence between tools. It does not explicitly state when not to use it or mention alternative listing tools, but the usage context is clear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.